1. Field of the Invention
The embodiments described herein relate generally to identifying a characteristic of an object and, more particularly, to identifying a CT value of an object in a container to facilitate detecting contraband concealed within the container.
2. Description of the Related Art
It is known to use computed tomography (CT) based explosive detection systems (EDS) to detect the presence of contraband. As used herein, the term “contraband” refers to any goods, such as an object and/or a material, that are unauthorized to possess, including, without limitation, explosives, weapons, drugs, and/or controlled substances. As described herein, contraband is contained within a container, such as a cargo container, a bag, a box, baggage, luggage, a carton, a crate, and/or any other suitable receptacle.
As is known, each 2D image slice is formed from a rectangular array of picture elements, or pixels. The numeric value of each pixel represents a CT value, which is an estimate of density. As used herein, a CT value is used as an estimate of density of a material, although the CT value is typically defined as an indication of an attenuation coefficient of the material rather than being a measure of the density of the material.
At least some known EDS CT systems use multi-row X-ray detectors that acquire a number of two-dimensional (2D) projections through the object while the object moves between the X-ray source and the detector. Some such systems use an image reconstruction algorithm that consists of selecting a number of 2D image slices and selecting (using an algorithm) detector data that allows reconstructing the CT density data in the 2D slices through a container. Such systems may be referred to as implementing “multi-slice” algorithms. For example, multi-slice algorithms include advanced single-slice rebinning (ASSR) and ray consistency reconstruction (RCR). Multi-slice algorithms are inexact algorithms and are known to produce lower image quality reconstruction than more exact methods, such as Katsevich helical 3D reconstruction.
In at least some known analysis methods, the analysis of each image slice includes segmenting, or grouping together, contiguous pixels into regions. Regions within the different 2D image slices are then compared and grouped into image objects representing physical objects within the container.
At least some other known CT reconstruction algorithm systems generate full volume data through the use of a cone beam reconstruction algorithm. Instead of interpolating projection data onto the 2D surfaces, as is done in a multi-slice algorithm, a cone beam algorithm reconstructs directly the full, three dimensional (3D) representation of a scanned container. As is known, the volume is represented in the volume data by volume elements, or voxels. The numeric value of each voxel is a CT value. Similar to the 2D image analysis method, during at least one known 3D image analysis of the volume data, contiguous voxels with a similar CT value are grouped together into image objects that represent characteristics, such as a size, a shape, and an approximate density, of a physical object within the container. Rules are applied to the measurements of the image object, such as a density, a volume, a mass, and/or a shape, to determine if the physical object is contraband and/or another item of interest.
Cone beam algorithms are known to produce higher quality (e.g., higher resolution) output at the expense of increased computing requirements. Specifically, cone beam reconstruction of a given object requires the execution of significantly more processor instructions than are required for multi-slice reconstruction of the same object. In some contexts (e.g., where real-time scanning is required), one may opt for multi-slice reconstruction, despite the lower quality output. Because some forms of contraband, such as sheet explosives, are difficult to detect with a multi-slice algorithm, an alarm is produced for containers having areas falling within a relatively broad target range of CT values. The use of such a broad target range increases the occurrence of false alarms and the attendant cost of manual inspection. Conversely, narrowing the target range increases the occurrence of false negatives and the risk that contraband will go undetected.